Building Maps with Genetic Algorithms
Project files
Abstract:
We address the problem of automatically designing maps for
first-person shooter (FPS) games. An efficient solution to
this procedural content generation (PCG) problem could allow
the design of FPS games of lower development cost with
near-infinite replay value and capability to adapt to the
skills and preferences of individual players. We propose a
search-based solution, where maps are evolved to optimize a
fitness function that is based on the players' average
fighting time. For that purpose, four different map
representations are tested and compared. Results obtained
showcase the clear advantage of some representations in
generating interesting FPS maps and demonstrate the promise
of the approach followed for automatic level design in that
game genre.
Interesting Points:
Evolving FPS maps with genetic algorithms
Evaluation function is average time-per-life of AI bot
modified by the amount of free space in the map
Four different 'representations' (map generating methods)